Development of ET SEBAL model in Google Earth Engine

Development of ET SEBAL model in Google Earth Engine

Published 6/2023

Created by GIS Lab

MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch

Genre: eLearning | Language: English | Duration: 86 Lectures ( 10h 41m ) | Size: 6 GB

What you'll learn

SEBAL

Evapotranspiration

Google Earth Engine

Remote Sensing

NDVI, SAVI, LAI

Surface Temperature

Incoming Longwave Radiation

Incoming Shortwave Radiation

Surface Emissivity

Momentum Roughness Length

Sensible Heat Flux

Soil Heat Flux

Outgoing longwave radiation

Net radiation flux

Requirements

Basic (or better Intermediate) knowledge of Google Earth Engine

Good Internet Connection

Description

In this course, you will master a step-by-step guide to developing a script in Google Earth Engine for the most famous Evapotranspiration model - Surface Energy Balance Algorithm for Land (SEBAL) for agricultural areas. Before starting a course, please read the requirements for the course - you need to have a Google Earth Engine profile (free to open), and a basic or better intermediate level of scripting in GEE or javascript. As a research study area an agricultural field that is located in Dubai Emirate, the UAE was taken. You can apply this course to your study area by making minor changes. It is good if you also have some knowledge/ experience of evapotranspiration. The course is divided into a theoretical part and a practical part, the latter of which constitutes almost 90 % of the course. Each practical part of the course contains an attached script in txt format. After finishing the course, besides developing the SEBAL model, you can apply different parts of the course in your other projects, that involve remote sensing. The course also contains two QGIS plugins ( to calculate instantaneous reference evapotranspiration and correlation coefficients) developed deliberately for the course which is free to download. Get ready to boost your knowledge in remote sensing and Google Earth Engine!

Who this course is for

Remote sensing specialists

GIS specialists

Remote sensing master students

GIS master students

Hydrologists

Ecologists

Crop scientists

Ecologists

Environmentalists